G01JDF calculates the lower tail probability for a linear combination of (central) variables.
Let
be independent Normal variables with mean zero and unit variance, so that
have independent
-distributions with unit degrees of freedom. G01JDF evaluates the probability that
If
this is equivalent to the probability that
Alternatively let
then G01JDF returns the probability that
Two methods are available. One due to
Pan (1964) (see
Farebrother (1980)) makes use of series approximations. The other method due to
Imhof (1961) reduces the problem to a one-dimensional integral. If
then a non-adaptive method
described in
D01BDF
is used to compute the value of the integral otherwise
D01AJF
is used.
Pan's procedure can only be used if the
are sufficiently distinct; G01JDF requires the
to be at least
distinct; see
Section 8. If the
are at least
distinct and
, then Pan's procedure is recommended; otherwise Imhof's procedure is recommended.
Farebrother R W (1980) Algorithm AS 153. Pan's procedure for the tail probabilities of the Durbin–Watson statistic Appl. Statist. 29 224–227
Imhof J P (1961) Computing the distribution of quadratic forms in Normal variables Biometrika 48 419–426
Pan Jie–Jian (1964) Distributions of the noncircular serial correlation coefficients Shuxue Jinzhan 7 328–337
- 1: METHOD – CHARACTER(1)Input
On entry: indicates whether Pan's, Imhof's or an appropriately selected procedure is to be used.
- Pan's method is used.
- Imhof's method is used.
- Pan's method is used if
, for are at least distinct and ; otherwise Imhof's method is used.
Constraint:
, or .
- 2: N – INTEGERInput
On entry: , the number of independent standard Normal variates, (central variates).
Constraint:
.
- 3: RLAM(N) – REAL (KIND=nag_wp) arrayInput
On entry: the weights,
, for , of the central variables.
Constraint:
for at least one
. If
, then the
must be at least
distinct; see
Section 8, for
.
- 4: D – REAL (KIND=nag_wp)Input
On entry: , the multiplier of the central variables.
Constraint:
.
- 5: C – REAL (KIND=nag_wp)Input
On entry: , the value of the constant.
- 6: PROB – REAL (KIND=nag_wp)Output
On exit: the lower tail probability for the linear combination of central variables.
- 7: WORK() – REAL (KIND=nag_wp) arrayWorkspace
- 8: IFAIL – INTEGERInput/Output
-
On entry:
IFAIL must be set to
,
. If you are unfamiliar with this parameter you should refer to
Section 3.3 in the Essential Introduction for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value
is recommended. If the output of error messages is undesirable, then the value
is recommended. Otherwise, if you are not familiar with this parameter, the recommended value is
.
When the value is used it is essential to test the value of IFAIL on exit.
On exit:
unless the routine detects an error or a warning has been flagged (see
Section 6).
If on entry
or
, explanatory error messages are output on the current error message unit (as defined by
X04AAF).
On successful exit at least four decimal places of accuracy should be achieved.
For the situation when all the
are positive
G01JCF may be used. If the probabilities required are for the Durbin–Watson test, then the bounds for the probabilities are given by
G01EPF.